Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Seasonal variation of anti-resa/Pf155 Plasmodium falciparum antibodies in three localities from the state of Amapá, Brazil

Anti-RESA/Pf155 antibodies were assayed in sera of individuals from three localities (Laranjal do Jari, Vila Padaria and Vila Paraíso) in the State of Amapá, Brazil, during the long-rains and short-rains seasons. All of these had negative blood smears for malaria. Most of the sera collected were positive in Indirect Fluorescent Antibody (IFA) with P. falciparum parasites, with no seasonal variation. A high percentage of these sera (62% to 100%) was RESA positive by Modified Indirect Fluorescent Antibody (MIFA), with a significant (p < 0.05) increase of geometric mean titers during the short-rains season, when the transmission of the disease is highest. ELISA with three repetitive RESA peptides (EENV)3 (4x3), (EENVEHDA)2 (8x2) and (DDEHVEEPTVA)2(11x2) did not reveal statistically significant seasonal variations, although a small enhancement of positivity was observed in V. Padaria (15.3 to 38.8%) in the short-rains season with the 8x2 peptides, and with 4x3 and 8x2 peptides in V. Paraíso, with a decrease in 11x2. MIFA titers appeared to be correlated mainly to the peptide 4x3 and it was the immunodominant in the three localities.

Surveillance of arbovirus infections in the atlantic forest region, State of São Paulo, Brazil: I. detection of hemagglutination-inhibition antibodies in wild birds between 1978 and 1990

We report data related to arbovirus antibodies detected in wild birds periodically captured from January 1978 to December 1990 in the counties of Salesópolis (Casa Grande Station), Itapetininga and Ribeira Valley, considering the different capture environments. Plasmas were examined using hemagglutination-inhibition (HI) tests. Only monotypic reactions were considered, except for two heterotypic reactions in which a significant difference in titer was observed for a determined virus of the same antigenic group. Among a total of 39,911 birds, 269 birds (0.7%) belonging to 66 species and 22 families were found to have a monotypic reaction for Eastern equine encephalitis (EEE), Venezuelan equine encephalitis (VEE), Western equine encephalitis (WEE), Ilheus (ILH), Rocio (ROC), St. Louis encephalitis (SLE), SP An 71686, or Caraparu (CAR) viruses. Analysis of the data provided information of epidemiologic interest with respect to these agents. Birds with positive serology were distributed among different habitats, with a predominance of unforested habitats. The greatest diversity of positive reactions was observed among species which concentrate in culture fields.

Multi-scale vegetation classification using earth observation data of the Sundarban mangrove forest, Bangladesh.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Integration of forest fire management with SDI: user requirements.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Clinical patterns and seasonal trends in respiratory syncytial virus hospitalizations in São Paulo, Brazil

The respiratory viruses are recognized as the most frequent lower respiratory tract pathogens for infants and young children in developed countries but less is known for developing populations. The authors conducted a prospective study to evaluate the occurrence, clinical patterns, and seasonal trends of viral infections among hospitalized children with lower respiratory tract disease (Group A). The presence of respiratory viruses in children's nasopharyngeal was assessed at admission in a pediatric ward. Cell cultures and immunofluorescence assays were used for viral identification. Complementary tests included blood and pleural cultures conducted for bacterial investigation. Clinical data and radiological exams were recorded at admission and throughout the hospitalization period. To better evaluate the results, a non- respiratory group of patients (Group B) was also constituted for comparison. Starting in February 1995, during a period of 18 months, 414 children were included- 239 in Group A and 175 in Group B. In Group A, 111 children (46.4%) had 114 viruses detected while only 5 children (2.9%) presented viruses in Group B. Respiratory Syncytial Virus was detected in 100 children from Group A (41.8%), Adenovirus in 11 (4.6%), Influenza A virus in 2 (0.8%), and Parainfluenza virus in one child (0.4%). In Group A, aerobic bacteria were found in 14 cases (5.8%). Respiratory Syncytial Virus was associated to other viruses and/or bacteria in six cases. There were two seasonal trends for Respiratory Syncytial Virus cases, which peaked in May and June. All children affected by the virus were younger than 3 years of age, mostly less than one year old. Episodic diffuse bronchial commitment and/or focal alveolar condensation were the clinical patterns more often associated to Respiratory Syncytial Virus cases. All children from Group A survived. In conclusion, it was observed that Respiratory Syncytial Virus was the most frequent pathogen found in hospitalized children admitted for severe respiratory diseases. Affected children were predominantly infants and boys presenting bronchiolitis and focal pneumonias. Similarly to what occurs in other subtropical regions, the virus outbreaks peak in the fall and their occurrence extends to the winter, which parallels an increase in hospital admissions due to respiratory diseases.

Seasonal variation of hepatitis A virus infection in the city of Rio de Janeiro, Brazil

Hepatitis A virus (HAV) infection constitutes a major public health problem in Brazil. The transmission of HAV is primarily by fecal-oral route so the water is an important vehicle of HAV dissemination. There is a great incidence of acute cases of hepatitis A in some areas of Brazil however the seasonal variation of these cases was not documented. The aim of this study was to determine the seasonality of HAV infection in Rio de Janeiro. From January 1999 to December 2001, 1731 blood samples were collected at the National Reference Center for Hepatitis Viruses in Brazil (NRCHV). These samples were tested by a commercial enzyme-immunoassay to detect anti-HAV IgM antibodies. Yearly positive rates were 33.74% in 1999, 32.19% in 2000, and 30.63% in 2001. A seasonal variation was recognized with the highest incidence in spring and summer. Furthermore a seasonal increase in incidence of HAV infection was found during the rainy season (December to March) because the index of rains is very high. It is concluded that HAV infections occur all year round with a peak during hot seasons with great number of rains.

Distributed Forest Fire Monitoring Using Wireless Sensor Networks

Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

State Space Analysis of Forest Fires

This paper studies forest fires from the perspective of dynamical systems. Burnt area, precipitation and atmospheric temperatures are interpreted as state variables of a complex system and the correlations between them are investigated by means of different mathematical tools. First, we use mutual information to reveal potential relationships in the data. Second, we adopt the state space portrait to characterize the system’s behavior. Third, we compare the annual state space curves and we apply clustering and visualization tools to unveil long-range patterns. We use forest fire data for Portugal, covering the years 1980–2003. The territory is divided into two regions (North and South), characterized by different climates and vegetation. The adopted methodology represents a new viewpoint in the context of forest fires, shedding light on a complex phenomenon that needs to be better understood in order to mitigate its devastating consequences, at both economical and environmental levels.

Carrion's disease (Bartonellosis bacilliformis) confirmed by histopathology in the High Forest of Peru

Bartonellosis or Carrion's disease is endemic in some regions of Peru, classically found in the inter-Andean valleys located between 500 and 3200 meters above sea level. We report the case of a 43 year-old male patient, farmer, who was born in the Pichanaki district (Chanchamayo, Junin), located in the High Forest of Peru. He presented with disseminated, raised, erythematous cutaneous lesions, some of which bled. The distribution of these lesions included the nasal mucosa and penile region. Additionally subcutaneous nodules were distributed over the trunk and extremities. Hematologic exams showed a moderate anemia. Serologic studies for HIV and Treponema pallidum were negative. The histopathologic results of two biopsies were compatible with Peruvian wart. Oral treatment with ciprofloxacin (500 mg BID) was begun. Over 10 days, the patient showed clinical improvement. This is the first report of a confirmed case of bartonellosis in the eruptive phase originating from the Peruvian High Forest, showing the geographical expansion of the Carrion's disease.

Forest fire detection with a small fixed wing autonomous aerial vehicle

In this work a forest fire detection solution using small autonomous aerial vehicles is proposed. The FALCOS unmanned aerial vehicle developed for remote-monitoring purposes is described. This is a small size UAV with onboard vision processing and autonomous flight capabilities. A set of custom developed navigation sensors was developed for the vehicle. Fire detection is performed through the use of low cost digital cameras and near-infrared sensors. Test results for navigation and ignition detection in real scenario are presented.

Studies on entomological monitoring: mosquito species frequency in riverine habitats of the Igarapava Dam, Southern Region, Brazil

Diversity of mosquito species was evaluated in different habitats before and after the Igarapava reservoir flooding in the Grande River, Southern Cerrado of Brazil. We aimed at verifying changes in these mosquito populations in consequence of the lake formation. Four habitats were selected as sampling stations: peridomiciliary habitat, pasture, "veredas" and gallery forest patch. Bimonthly collections were made with the Shannon trap and human bait, including diurnal, crepuscular and nocturnal period of mosquito activity. The Shannon Index results from the potential vectors were compared using Student t-test. Aedes scapularis, Anopheles darlingi and An. albitarsis senso latu seasonal abundance were described with moving average and compared using chi2 test. There were changes in the mosquito frequency in the habitats, except for the "veredas" that was 13 km away from the catchment area. The altering in mosquito species seasonal abundance suggests breeding places expansion. Diversity indexes can be used to monitor changes in mosquito vector population in environments where abrupt disturbance can alter disease transmission cycles.

Fractional Dynamics in Forest Fires

Every year forest fires consume large areas, being a major concern in many countries like Australia, United States and Mediterranean Basin European Countries (e.g., Portugal, Spain, Italy and Greece). Understanding patterns of such events, in terms of size and spatiotemporal distributions, may help to take measures beforehand in view of possible hazards and decide strategies of fire prevention, detection and suppression. Traditional statistical tools have been used to study forest fires. Nevertheless, those tools might not be able to capture the main features of fires complex dynamics and to model fire behaviour [1]. Forest fires size-frequency distributions unveil long range correlations and long memory characteristics, which are typical of fractional order systems [2]. Those complex correlations are characterized by self-similarity and absence of characteristic length-scale, meaning that forest fires exhibit power-law (PL) behaviour. Forest fires have also been proved to exhibit time-clustering phenomena, with timescales of the order of few days [3]. In this paper, we study forest fires in the perspective of dynamical systems and fractional calculus (FC). Public domain forest fires catalogues, containing data of events occurred in Portugal, in the period 1980 up to 2011, are considered. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses. The frequency spectra of such signals are determined using Fourier transforms, and approximated through PL trendlines. The PL parameters are then used to unveil the fractional-order dynamics characteristics of the data. To complement the analysis, correlation indices are used to compare and find possible relationships among the data. It is shown that the used approach can be useful to expose hidden patterns not captured by traditional tools.